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View article: Agentic AI for Computer Vision: A Review
Agentic AI for Computer Vision: A Review Open
General Computer vision models operate as passive systems that produce one output and stop, while agentic AI for computer vision represents a shift toward autonomous visual decision-making systems. In such systems, visual input is used to …
View article: An integrated deep learning framework using adaptive enhanced vision fusion and modified mobilenet architecture for precision classification of skin diseases with enhanced diagnostic performance
An integrated deep learning framework using adaptive enhanced vision fusion and modified mobilenet architecture for precision classification of skin diseases with enhanced diagnostic performance Open
Due to challenges such as illumination variability, noise, and visual distortions, machine learning (ML) and deep learning (DL) approaches for skin disease evaluation remain complex. Traditional methods often neglect these issues, leading …
View article: Enhancing Mental Health Decision-Making with Artificial Intelligence/Machine Learning: A Prescriptive Analytics Approach for Customised Outcomes
Enhancing Mental Health Decision-Making with Artificial Intelligence/Machine Learning: A Prescriptive Analytics Approach for Customised Outcomes Open
Depression is a complex and widespread mental health condition affecting over 280 million people globally, yet access to timely diagnosis and personalised treatment remains limited. This study explores the application of artificial intelli…
View article: Deep learning for land use classification: a systematic review of HS-LiDAR imagery
Deep learning for land use classification: a systematic review of HS-LiDAR imagery Open
Remote sensing (RS) technologies have significantly advanced Earth observation capabilities, enhancing the characterization and identification of surface materials through both spaceborne and airborne systems. These advancements are crucia…
View article: Beyond Data, Towards Sustainability: a Sydney Case Study On Urban Digital Twins
Beyond Data, Towards Sustainability: a Sydney Case Study On Urban Digital Twins Open
As urban areas grapple with unprecedented challenges stemming from population growth and climate change, the emergence of urban digital twins offers a promising solution. This paper presents a case study focusing on Sydney’s urban digital …
View article: PointDiffuse: A Dual-Conditional Diffusion Model for Enhanced Point Cloud Semantic Segmentation
PointDiffuse: A Dual-Conditional Diffusion Model for Enhanced Point Cloud Semantic Segmentation Open
Diffusion probabilistic models are traditionally used to generate colors at fixed pixel positions in 2D images. Building on this, we extend diffusion models to point cloud semantic segmentation, where point positions also remain fixed, and…
View article: PALQA: A Novel Parameterized Position-Aware Lossy Quantum Autoencoder using LSB Control Qubit for Efficient Image Compression
PALQA: A Novel Parameterized Position-Aware Lossy Quantum Autoencoder using LSB Control Qubit for Efficient Image Compression Open
With the growing interest in quantum computing, quantum image processing technology has become a vital research field due to its versatile applications and ability to outperform classical computing. A quantum autoencoder approach has been …
View article: Value Sensitive Design of Social Robots: Enhancing the Lives of LGBT+ Older Adults
Value Sensitive Design of Social Robots: Enhancing the Lives of LGBT+ Older Adults Open
The integration of care and social robots in aged care offers a promising solution to the increasing global challenges posed by an ageing population and caregiver shortages. While these robots have demonstrated promising outcomes in enhanc…
View article: An Overview of Quantum Circuit Design Focusing on Compression and Representation
An Overview of Quantum Circuit Design Focusing on Compression and Representation Open
Quantum image computing has attracted attention due to its vast storage capacity and faster image data processing, leveraging unique properties such as parallelism, superposition, and entanglement, surpassing classical computers. Although …
View article: Effective Land Use Classification Through Hybrid Transformer Using Remote Sensing Imagery
Effective Land Use Classification Through Hybrid Transformer Using Remote Sensing Imagery Open
Recent advances in deep learning for hyperspectral image (HSI) classification have shown exceptional performance in resource management and environmental planning through land use classification. Despite these successes, challenges continu…
View article: An Overview of the Quantum Circuit Design Focusing on Compression and Representation
An Overview of the Quantum Circuit Design Focusing on Compression and Representation Open
Quantum image computing has attracted attention due to its vast storage and faster processing of image data than classical computers. Although classical computing power has grown substantially in the last decade, its abilities have plateau…
View article: The impact of trauma-informed practices on academic outcomes of First Nations children: a pilot study of culturally responsive supports in Australia
The impact of trauma-informed practices on academic outcomes of First Nations children: a pilot study of culturally responsive supports in Australia Open
This pilot observational study examined the effectiveness of trauma-informed and culturally responsive behavior support practices on the academic outcomes of predominantly First Nations children in an Australian primary school. The researc…
View article: Organoid Computer Vision: A Survey and Outlook
Organoid Computer Vision: A Survey and Outlook Open
This paper introduces an intersection of computer vision, organoid biology, and artificial intelligence by naming it Organoid Computer Vision (OCV). OCV is emerging as an interdisciplinary field that leverages advanced computational techni…
View article: Power spectral density-based resting-state EEG classification of first-episode psychosis
Power spectral density-based resting-state EEG classification of first-episode psychosis Open
View article: Improved Video-Based Point Cloud Compression via Segmentation
Improved Video-Based Point Cloud Compression via Segmentation Open
A point cloud is a representation of objects or scenes utilising unordered points comprising 3D positions and attributes. The ability of point clouds to mimic natural forms has gained significant attention from diverse applied fields, such…
View article: Dark Transformer: A Video Transformer for Action Recognition in the Dark
Dark Transformer: A Video Transformer for Action Recognition in the Dark Open
Recognizing human actions in adverse lighting conditions presents significant challenges in computer vision, with wide-ranging applications in visual surveillance and nighttime driving. Existing methods tackle action recognition and dark e…
View article: Improving Hyperspectral Image Classification with Compact Multi-Branch Deep Learning
Improving Hyperspectral Image Classification with Compact Multi-Branch Deep Learning Open
The progress in hyperspectral image (HSI) classification owes much to the integration of various deep learning techniques. However, the inherent 3D cube structure of HSIs presents a unique challenge, necessitating an innovative approach fo…
View article: Beyond Data, Towards Sustainability: A Sydney Case Study on Urban Digital Twins
Beyond Data, Towards Sustainability: A Sydney Case Study on Urban Digital Twins Open
As urban areas grapple with unprecedented challenges stemming from population growth and climate change, the emergence of urban digital twins offers a promising solution. This paper presents a case study focusing on Sydney's urban digital …
View article: Video Anomaly Detection in 10 Years: A Survey and Outlook
Video Anomaly Detection in 10 Years: A Survey and Outlook Open
Video anomaly detection (VAD) holds immense importance across diverse domains such as surveillance, healthcare, and environmental monitoring. While numerous surveys focus on conventional VAD methods, they often lack depth in exploring spec…
View article: Neuromorphic Correlates of Artificial Consciousness
Neuromorphic Correlates of Artificial Consciousness Open
The concept of neural correlates of consciousness (NCC), which suggests that specific neural activities are linked to conscious experiences, has gained widespread acceptance. This acceptance is based on a wealth of evidence from experiment…
View article: Improved video-based point cloud compression via segmentation
Improved video-based point cloud compression via segmentation Open
Point cloud is a representation of objects or scenes utilising unordered points comprising 3D positions and attributes. The ability of point clouds to mimic natural forms has gained significant attention from diverse applied fields, such a…
View article: Soft Masked Transformer for Point Cloud Processing with Skip Attention-Based Upsampling
Soft Masked Transformer for Point Cloud Processing with Skip Attention-Based Upsampling Open
Point cloud processing methods leverage local and global point features %at the feature level to cater to downstream tasks, yet they often overlook the task-level context inherent in point clouds during the encoding stage. We argue that in…
View article: Spectrally Segmented-Enhanced Neural Network for Precise Land Cover Object Classification in Hyperspectral Imagery
Spectrally Segmented-Enhanced Neural Network for Precise Land Cover Object Classification in Hyperspectral Imagery Open
The paradigm shift brought by deep learning in land cover object classification in hyperspectral images (HSIs) is undeniable, particularly in addressing the intricate 3D cube structure inherent in HSI data. Leveraging convolutional neural …
View article: Accurate and Efficient Urban Street Tree Inventory with Deep Learning on Mobile Phone Imagery
Accurate and Efficient Urban Street Tree Inventory with Deep Learning on Mobile Phone Imagery Open
Deforestation, a major contributor to climate change, poses detrimental consequences such as agricultural sector disruption, global warming, flash floods, and landslides. Conventional approaches to urban street tree inventory suffer from i…
View article: A Deep Learning-Based Hyperspectral Object Classification Approach via Imbalanced Training Samples Handling
A Deep Learning-Based Hyperspectral Object Classification Approach via Imbalanced Training Samples Handling Open
Object classification in hyperspectral images involves accurately categorizing objects based on their spectral characteristics. However, the high dimensionality of hyperspectral data and class imbalance pose significant challenges to objec…
View article: Efficient quantum image representation and compression circuit using zero-discarded state preparation approach
Efficient quantum image representation and compression circuit using zero-discarded state preparation approach Open
Quantum image computing draws a lot of attention due to storing and processing image data faster than classical. With increasing the image size, the number of connections also increases, leading to the circuit complex. Therefore, efficient…
View article: Enabling Spatial Digital Twins: Technologies, Challenges, and Future Research Directions
Enabling Spatial Digital Twins: Technologies, Challenges, and Future Research Directions Open
A Digital Twin (DT) is a virtual replica of a physical object or system, created to monitor, analyze, and optimize its behavior and characteristics. A Spatial Digital Twin (SDT) is a specific type of digital twin that emphasizes the geospa…
View article: Advanced quantum image representation and compression using a DCT-EFRQI approach
Advanced quantum image representation and compression using a DCT-EFRQI approach Open
In recent years, quantum image computing draws a lot of attention due to storing and processing image data faster compared to classical computers. A number of approaches have been proposed to represent the quantum image inside a quantum co…
View article: Hyperspectral Image Classification via Information Theoretic Dimension Reduction
Hyperspectral Image Classification via Information Theoretic Dimension Reduction Open
Hyperspectral images (HSIs) are one of the most successfully used tools for precisely and potentially detecting key ground surfaces, vegetation, and minerals. HSIs contain a large amount of information about the ground scene; therefore, ob…
View article: Beyond Data, Towards Sustainability: A Sydney Case Study on Urban Digital Twins
Beyond Data, Towards Sustainability: A Sydney Case Study on Urban Digital Twins Open